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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Ahmad, Nazia Hussain, Sajithunisa Khan, Rubina Liyakat Quraishi, Suhail Javed Singh, Anupam George, Remya P. Applied College Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Mriirs Computer Applications Haryana Faridabad India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350380583

The current instigation aims to examine how AI and IoT work hand in hand to use smart home automation with a special focus on the application based on Arduino microcontrollers. The suggested system focuses on increasing comfort, convenience, and safety of the home spaces by applying AI algorithms. The system comprises a number of integrated sensors and actuators that gather real time data and the data is analyzed and decisions are made by an AI control module. The strategies of design considerations, implementation, and the assessment of the energy usage, comfort level for the user and the security aspects of the system are also provided in the study. Exploitation of the proposed experimental benchmark confirms potential advancement compared to traditional systems, including the viability of successful, comprehensive smart home platforms. Keywords: Smart Home Automation, Energy Efficiency, Internet of Things (10 T), Artificial Intelligence (AI), Arduino Uno © 2024 IEEE.

关键词： Smart homes

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Predicting opinion evolution based on information diffusion in social networks using a hybrid fuzzy based approach

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International Journal of Information Technology (Singapore) 2023年第1期15卷 87-100页

作者： Uthirapathy, Samson Ebenezar Sandanam, Domnic Department of Computer Applications National Institute of Technology Tamil Nadu Tiruchirappalli 620015 India Department of Computing Science and Engineering Vignan’s Foundation for Science Technology & Research Vadlamudi Andra Pradesh Guntur 522213 India

Social media plays an important role in disseminating information and analysing public and government opinions. The vast majority of previous research has examined information diffusion and opinion analysis separately. This study proposes a new framework for analysing both information diffusion and opinion evolution. The change in opinion over time is known as opinion evolution. To propose a new model for predicting information diffusion and opinion analysis in social media, a forest fire algorithm, cuckoo search, and fuzzy c-means clustering are used. The forest fire algorithm is used to determine the diffuser and non-diffuser of information in social networks, and fuzzy c-means clustering with the cuckoo search optimization algorithm is proposed to cluster Twitter content into various opinion categories and to determine opinion change. On different Twitter data sets, the proposed model outperformed the existing methods in terms of precision, recall, and accuracy. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer applications and Management.

关键词： Cuckoo search Forest fire algorithm Fuzzy C-means clustering Information diffusion Opinion analysis Social network

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An IOT based Framework for Project Management 13

An IOT based Framework for Project Management

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13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

作者： Kumar, Devendra Tewari, Pragya ABES Engineering College Department of Computer Applications Uttar Pradesh Ghaziabad India School of Computing Science & Engineering Dept of Computer Science & Engineering Galgotias University India

ISBN: (纸本)9781713857938

The Internet of Things is transforming the world due to which organizations are facing many difficulties. The transformation due to these technologies is affecting several areas and project management is not an exception. The Internet of Things can help project managers to manage their projects as well as their types of equipment in an effective way. The connection between IoT devices and project management can allow businesses to achieve new innovations and services in a more effective manner while reducing the risk factor. In this paper, we proposed a framework for effective project management based on the Internet of Things (IoT). © Grenze Scientific Society, 2022.

关键词： Project management

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Building Resilience in Shopping: Secure Shopping System for Pandemics Like Covid-19 4

Building Resilience in Shopping: Secure Shopping System for ...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Jeyapandi, S. Muthu, A. Essaki Vallileka, N. Niranjana, R. Saravanan, K. Sakthidevi, I. Scad College of Engineering and Technolog Department of Mechanical Engineering Cheranmahadevi India Scad College of Engineering and Technology Department of Computer Science and Engineering Cheranmahadevi India PSNA College of Engineering and Technology Department of Computer Applications Dindigul India Sri Krishna College of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India College of Engineering Anna University Department of Computer Science and Engineering Chennai India Adhiyamaan College of Engineering Department of Information Technology Hosur India

ISBN: (纸本)9798350300888

COVID-19 has affected the health condition of the people in India to a huge extent. The death rate seems to be high during the second wave of COVID-19 compared to the first wave. This is mainly due lethargic behaviour of the people. People fail to maintain social distancing and fail to wear the mask at public places. This has led to increase in spread of the disease. Government has announced the lockdown with some relaxations given to people to purchase the groceries with time restrictions. People tend to rush towards Supermarket to purchase groceries. This may further lead to increase in severity of the spread. Hence, the study proposes a secured system shopping which follows two-way screening process before letting the people into the super market. This system also proposed a smart shopping procedure which prevents excess billing time at the payment counter. Hence this system proves to be very effective in preventing the spread of the disease to a huge extent. © 2023 IEEE.

关键词： COVID-19

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Secure Digital Image Watermarking Technique Based on ResNet-50 Architecture

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Intelligent Automation & Soft Computing 2024年第6期39卷 1073-1100页

作者： Satya Narayan Das Mrutyunjaya Panda Department of Computer Science and Engineering GIET UniversityGunupurOdisha765022India Department of Computer Science and Applications Utkal UniversityBhubaneswarOdisha751004India

In today’s world of massive data and interconnected networks,it’s crucial to burgeon a secure and efficient digital watermarking method to protect the copyrights of digital *** research primarily focuses on deep learning-based approaches to improve the quality of watermarked images,but they have some *** overcome this,the deep learning digital image watermarking model with highly secure algorithms is proposed to secure the digital ***,quantum logistic maps,which combine the concept of quantum computing with traditional techniques,have been considered a niche and promising area of research that has attracted researchers’attention to further research in digital *** research uses the chaotic behaviour of the quantum logistic map with Rivest–Shamir–Adleman(RSA)and Secure Hash(SHA-3)algorithms for a robust watermark embedding process,where a watermark is embedded into the host *** way,the quantum chaos method not only helps limit the chance of tampering with the image content through reverse engineering but also assists in maintaining a high level of imperceptibility and strong robustness with efficient extraction or detection of watermark *** Wavelet Transformation(LWT)is a potential and computationally efficient version of traditional Discrete Wavelet Transform(DWT)where the host image is divided into four sub-bands to offer a multi-resolution view of an image with greater flexibility in watermarking ***,considering the robustness against attacks,a pre-trained Residual Neural Network(ResNet-50),a convolutional neural network with 50 layers deep,is used to better learn the complex features and efficiently extract the watermark from the *** integrating RSA and SHA-3 algorithms,the proposed model demonstrates improved imperceptibility,robustness,and accuracy in watermark extraction compared to traditional *** achieves a Peak Signal-to-Noise Ratio(PSNR)of 49.83%,a Structural Simi

关键词： Image watermarking quantum logistics Rivest-Shamir-Adleman(RSA) Secure Hash(SHA-3) Lifting Wavelet Transformation(LWT) ResNet-50 deep learning secure communication

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Automated Detection of Language Disorders in Children Using NLP and Machine Learning

Automated Detection of Language Disorders in Children Using ...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Malathi, P. Legapriyadharshini, N. Nair, Shruthi S Sujatha, M.P. Sadaieswaran, R. Thirumalaikumari, T. Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Data Analytics Tamil Nadu Chennai India Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Application Tamil Nadu Chennai India Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Agni College of Technology Department of Computer Science and Engineering Chennai India Tagore College of Arts and Science Department of Computer Applications Chennai India Simats Deemed to Be University Saveetha College of Liberal Arts and Sciences Department of Computer Science Chennai India

ISBN: (纸本)9798350309140

The purpose of the study is to address the essential need for a more efficient and objective technique for detecting language disorders in children, overcoming the constraints of standard manual evaluation systems. Existing systems, which utilize subjective evaluations and manual scoring, frequently result in lengthy processes and possible errors. To solve these issues, the proposed system automates the identification process by combining Natural Language Processing (NLP) and Machine Learning (ML). The system achieves a breakthrough in accuracy by normalizing text and extracting a comprehensive collection of linguistic features using advanced NLP techniques. The implementation involves difficult data preprocessing, extensive feature extraction, and the application of a cutting-edge Support Vector Machine (SVM) classifier. The proposed system achieves a 15% increase in accuracy, a 12% increase in precision, a 10% increase in recall, and an 11% increase in F1 score over existing systems. The confusion matrices show improved prediction skills, while accuracy across varied linguistic samples demonstrates the system's adaptability. Finally, the proposed system not only speeds up the detection of language disorders but also provides the groundwork for deeper insights into linguistic development, with revolutionary potential in educational and therapeutic settings. © 2024 IEEE.

关键词： Adversarial machine learning

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GUARDEV: Guided Unified Adaptive Response for Defending Electric Vehicles 27th

GUARDEV: Guided Unified Adaptive Response for Defending Elec...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Mondal, Koustav Kumar Das, Debasis Inter-Disciplinary Research Division - IoT and Applications Indian Institute of Technology Jodhpur Rajasthan Jodhpur India Department of Computer Science Engineering Indian Institute of Technology Jodhpur Rajasthan Jodhpur India

ISBN: (纸本)9783031783821

In the rapidly evolving landscape of electric vehicles (EVs), integrating the Internet of Vehicles (IoV) has opened up new dimensions in automotive technology. While enhancing vehicle performance, safety, and security, this advancement also exposes EVs to heightened cyber threats. To address this critical concern, we introduce GUARDEV: Guided Unified Adaptive Response for Defending Electric Vehicles, a novel Machine Learning (ML)-enhanced conflict resolution-based ensemble Intrusion Detection System (IDS) architecture. GUARDEV leverages the power of adaptive ML techniques to provide a unified and guided response in safeguarding EVs against sophisticated cyber-attacks. Our framework evaluates the effectiveness of three prominent ML models - XGBoost, Random Forest, and Extra Trees - in detecting specific categories of cyber threats. By harnessing the prediction confidence scores from these models, GUARDEV offers a nuanced and intelligent approach to recognizing and thwarting diverse cyber-attacks. Our research, grounded in rigorous experimentation using public IoV security datasets, demonstrates GUARDEV’s exceptional accuracy of 99.47% in intrusion detection. This remarkable achievement not only underscores the potential of ML in enhancing vehicular cybersecurity but also establishes GUARDEV as a powerful tool for creating safer, more secure EVs. GUARDEV paves the way for robust protection of internet-connected electric vehicles in today’s digital age by providing a guided, unified, and adaptive response to cyber threats. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Network intrusion

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Comparative Analysis of Multilingual and Cross-Lingual Models for Aspect-Based Sentiment Analysis 13

Comparative Analysis of Multilingual and Cross-Lingual Model...

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Hussain, Sajithunisa Khan, Rubina Liyakat Quraishi, Suhail Javed Singh, Anupam George, Remya P. Ahmad, Nazia Applied College Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Computer Applications Mriirs Haryana Faridabad India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350380583

Aspect-Based Sentiment Analysis (ABSA) is a finegrained sub-task of Natural Language Processing concerned with opinion bearing on certain aspects contained in text. The shift towards multicultural content on the digital platforms implies the need to have models which will perform the sentiment analysis of the multilingual content. In this study, a detailed comparison of ten developed methodologies of ABSA models is presented, including the theoretical background, data sets, and the assessment of performances of each model. We explore various techniques that are based on the lexical resources, statistical and machine learning, and state of the art deep learning networks. The study also sheds light on the potential strength and weakness of the proposed method and points out the possible further research directions that can be undertaken for improving the multilingual or cross-lingual sentiment analysis. © 2024 IEEE.

关键词： Contrastive Learning

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Artistic Style Transfer Using Generative Adversarial Networks: A Pix2Pix Implementation

Artistic Style Transfer Using Generative Adversarial Network...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Kumar, Dubasi Pavan Bhadula, Shuchi Al-Farouni, Mohammed Varshney, Neeraj Sharma, Vishal Saraswat, Manish National Institute Of Technology Integrated Master Of Science Mathematics Department Of Mathematics Patna India Graphic Era Deemed To Be University Department Of Computer Science & Engineering Dehradun India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Gla University Department Of Computer Engineering And Applications Mathura India Lovely Professional University Phagwara India Lloyd Institute Of Engineering & Technology Greater Noida India

ISBN: (纸本)9798350366846

This investigation explores the viability of four noticeable models, specifically Pix2Pix, Neural Style Transfer (NST), Fast Neural Style Transfer (FastNST), and CycleGAN, within the space of aesthetic style exchange. The think about envelops a fastidious assessment of these models, investigating their capabilities in generating outwardly engaging and elaborately reliable pictures. Through broad tests and quantitative evaluations, Pix2Pix developed as a strong choice, accomplishing a Crest Signal-to-Noise Ratio (PSNR) of 26.78 dB, a Basic Likeness List (SSIM) of 0.832, and a Fréchet Initiation Separate (FID) of 54.21. NST, exceeding expectations in style devotion, achieved a PSNR of 29.45 dB, an SSIM of 0.905, and an FID of 72.03. FastNST, known for its real-time preparation, illustrated an adjusted execution with a PSNR of 28.12 dB, an SSIM of 0.892, and an FID of 68.54. CycleGAN, outlined for unpaired picture interpretation, accomplished a PSNR of 27.65 dB, an SSIM of 0.874, and an FID of 63.72. The results give profitable experiences into the comparative qualities and weaknesses of these models, educating their appropriateness in different artistic assignments. © 2024 IEEE.

关键词： Generative adversarial networks

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Predicting Early Possibilities of Breast Cancer Detection Using Machine Learning Techniques 13

Predicting Early Possibilities of Breast Cancer Detection Us...

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Khan, Rubina Liyakat Quraishi, Suhail Javed Singh, Anupam George, Remya P. Ahmad, Nazia Hussain, Sajithunisa Imam Abdulrahman Bin Faisal University Applied College Dammam Saudi Arabia Mriirs Computer Applications Haryana Faridabad India Graphic Era Hill University Department of Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350380583

Breast cancer is one of the imperative health concerns affecting women globally, and early diagnosis can help to enhance the prognosis for the cases and patients. The main concern of the current study is to use machine learning algorithms to analyze the dataset of features of breast cancer and predict whether or not they are malignant. In the pre-processing step, we implemented basic steps and on classification steps, we applied several classification algorithms such as Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and kNearest Neighbor. Among all the classifiers, the Random Forest classifier had the highest estimated accuracy. The paper also brings into prominence the features which are selected and the affect of different sorts of machine learning etc in the diagnosis of the disease. © 2024 IEEE.

关键词： Adversarial machine learning

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